The framework introduced in this paper aims to reflect the characteristics that social machines have been described to have. The framework uses a mixed methods approach underpinned by social theory to provide a detailed and rich understanding of the socio-technical nature of a social machine. The strength of this lies in the diversity of the data being used; whilst the quantitative approach can provide mathematical rigor to the structure and properties of the networks and appreciate its scale, the qualitative approach seeks to examine the 'social relations', and the context to how the social machine is enabling humans and technologies to interact and shape each other. Like many studies using empirical-based research, this framework takes advantage of the complementary nature that mixed methods offers, and pushes it further by using an analytical socio-technical lens.<br/

Carr, Les

Tinati, Ramine

English

Ramine Tinati

Leslie Carr

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Understanding Social Machines

Southampton (e-Prints Soton)

Understanding Social Machines  Ramine Tinati, Leslie Carr Electronics and Computer Science University of Southampton Southampton, United Kingdom {rt506, lac}@ecs.soton.ac.uk   Keywords-Social  Machines;  Social  Theory;  Methodology; Framework; Web Science I.   EXTENDED ABSTRACT The  Web  is  an  evolving,  complex  socio-technical  system [1].  As  a  social  technology  [2],  the  Web  is  a  diverse collection  of  interacting  networks  of  activities  and communities. The openness and scalability of the Web has provided  a  platform  for  new  technologies,  services  and standards,  enabling  individuals  at  scale  to  connect, communicate  and  share  in  ways  that  were  previously impractical. The Web has enabled new forms of activity to emerge  and  grow;  a  new  area  of  Web  activity  is  the development of social computing and social machines [3]. This new area of activity harnesses the power of the crowd to  perform  computationally  difficult  and  time  consuming tasks.  Before Web technologies provided a platform to perform such  tasks,  the  Internet  offered  a  network  of  distributed computing power to perform computationally intense tasks [4]. Unlike Web based systems, the design of Internet based systems did not require individuals to directly spend their time operating them, yet they were still a social machine of sorts. Users were required to actively consent to download and  install  software  and  use  their  idle  CPU  and  network bandwidth. The success of these social machines were the result  of  the  heterogeneous  networks  of  human  and technologies  interacting  and  working  together;  these machines relied no only on the technology working, but the acceptance  and  adoption  of  a  new  social  process  by  the individual. It becomes clear that examining the relationship between society and technology, any task that requires the co-constitutional involvement of humans and technologies is a form of social machine, and to this ends, no more so than the Web itself. There just exist different scales of social machinery. Examining  the  scales  of  social  machines,  they  range from  the  lightweight  to  heavyweight  [5].  Those  that  are lightweight  could  be  described  as  exhibiting  strict, deterministic  characteristics,  harnessing  the  collective problem  solving  capabilities  of  humans  to  perform computationally  hard  processes  [6][7].  Less  deterministic are  middleweight  social  machines,  exhibiting  a  mix  of lightweight and heavyweight characteristics [8]; lightweight in  regards  to  the  crowdsource  techniques  employed,  yet heavyweight  in  terms  of  the  pre-exiting  structures  and hierarchy of power that ultimately, make the final decisions. At the heavyweight end of the scale are machines that exist as a result of the interactions between human creativity and technological capabilities, a relationship which is mutually reinforcing  [3],  power  between  the  user  and  engineer  is distributed, and users  are crucial in the  machines success and shape the overall goals and purpose of the system [5].  A common characteristic that is shared amongst social machines of all scales is  their socio-technical  structure, a network  of  actors  that  relies  on  the  co-constructive  relationships between society and technology [1]. As these machines  grow  and  evolve,  they  enroll  more  users,  more technologies, and consequently, more issues.  The  development  of  a  social  machines  is  in  some respects a reflection of the process of the Web [9]; an idea is developed  in  a  controlled  environment,  and  although  is subject  to  the  same  socio-technical  processes  of  any technological development, the actors involved within this stage are well defined and somewhat restricted. However, when the shift from the micro to the macro occurs–from the controlled  environment  to  the  unknowns  of  the  Web–the original  actors  are  no  longer  in  control;  consequently  the social machine becomes just another Web activity. Therein lies  the  problem,  we  currently  have  no  methods  to understand  and  describe  the  social  machines  during  and after its development; this not only at the micro level–which itself is important–but at the macro level, when it enters the wilderness of the Web, a Web full of unknowns, competing technologies,  diverse  users  and  constantly  changing networks of activity. To address this, we have developed a novel approach to understanding  and  guiding  the  development  of  social machines. The  framework,  shown in Fig. 1, combines an applied social theory with a mixed methods approach, which takes advantage of not only the richness and complementary analytical  strengths  that  using  both  quantitative  and qualitative  data  sources  provide  [10],  but  also  the epistemological and ontological position of Actor Network Theory (ANT), offering an analytical lens  to interpret and understanding how socio-technical networks function. ANT provides the language and ontological concepts to explore the  structure  and  formation  of  the  Web  activity  being studied, based upon ANT’s perspective on the formation of actor-networks,  their  transient  characteristics,  and  their ability to grow, change shape, and join with other networks [11].  Drawing  upon  a  mixed  methods  approach,  the development of a social machine can be examined in terms of  the  different  stages  of  translation  it  goes  through, examining how the socio-technical activities of the actors enabled the network to translate and reach a potential point of  stability.  By  using  the  process  of  translation  as  a framework to identify and separate a number of different processes  required  for  the  successful  formation  of  a network,  it  provides  a  method  to  apply  metrics  to  pro-actively  and  reactively  understand  and  support  the network’s success.  At each stage of translation, a number of data collection techniques  which  are  based  on  quantitative  and/or qualitative  data  sources  can  be  used,  providing  evidence based  explanations  to  the  interactions  and  outcomes  that result. The framework facilitates a process what might be described by analogy as “social machine engineering”.  II.  CONCLUDING REMARKS This framework introduced in this paper aims to reflect the characteristics that social machines have been described to have.  The  framework  uses  a  mixed  methods  approach underpinned by social theory to provide a detailed and rich understanding  of  the  socio-technical  nature  of  a  social machine. The strength of this lies in the diversity of the data being  used;  whilst  the  quantitative  approach  can  provide mathematical  rigor  to  the  structure  and  properties  of  the networks and appreciate its scale, the qualitative approach seeks to examine the ‘social relations’ [12], and the context to  how  the  social  machine  is  enabling  humans  and technologies to interact and  shape each other.  Like  many studies using empirical-based research [10], this framework takes  advantage  of  the  complementary  nature  that  mixed methods offers, and pushes it further by using an analytical socio-technical lens.  III.  ACKNOWLEDGEMENTS This  research  was  funded  by  the  Research  Councils  UK Digital  Economy  Programme,  Web  Science  Doctoral Training Centre, EP/G036926/1.  REFERENCES  [1]  S. Halford, C. Pope, and L. Carr, “A Manifesto for Web Science?,” Proceedings of the Web Science 2009, pp. 1-6, 2009. [2]  T. Berners-Lee, D. J. Weitzner, W. Hall, K. O’Hara, N. Shadbolt, and J. a. Hendler, “A Framework for Web Science,” Foundations and Trends® in Web Science, vol. 1, no. 1, pp. 1-130, 2006. [3]  J. Hendler and T. Berners-Lee, “From the Semantic Web to social machines: A research challenge for AI on the World Wide Web,” Artificial Intelligence, vol. 174, no. 2, pp. 156-161, Feb. 2010. [4]  S. M. Larson, C. D. Snow, M. Shirts, and V. S. Pande, “Folding@Home and Genome@Home: Using distributed computing to tackle previously intractable problems in computational biology,” Security, 2009. [5]  C. Haythornthwaite, “Crowds and Communities : Light and Heavyweight Models of Peer Production,” pp. 1-10, 2009. [6]  W. Roush, “Social Machines: Computing means connecting,” Technology Review Published by MIT, vol. 2005, no. 3 August, 2005. [7]  F. Guinchiglia and D. Robertson, “The Social Computer - Combining Machine and Human,” Computer, no. May, 2010. [8]  M. J. Raddick et al., “Galaxy Zoo: Exploring the Motivations of Citizen Science Volunteers,” Astronomy Education Review, vol. 9, no. 1, p. 010103, 2010. [9]  T. Berners-Lee, “The Two Magics of Web Science,” in Keynote Speech at 16th International World Wide Web Conference (WWW2007), 2007. [10]  J. E. M. Sale and K. Brazil, “Revisiting the Quantitative-Qualitative Debate : Implications for Mixed-Methods Research,” Community Health, pp. 43-53, 2002. [11]  B. Latour, Reassembling the Social: An Introduction to Actor-Network-Theory by Bruno Latour, vol. 10, no. 3. Oxford University Press, 2005. [12]  R. S. Burt, “Applied Network Analysis: An Overview,” Sociological Methods Research, vol. 7, no. 2, pp. 123-130, 1978.   Figure 1.  The Process of the Web 

A Manifesto for Web Science?,”

Applied Network Analysis: An Overview,”

Crowds and Communities Light and Heavyweight Models of Peer Production,”

Folding@Home and Genome@Home: Using distributed computing to tackle previously intractable problems in computational biology,” Security,

From the Semantic Web to social machines: A research challenge for

Galaxy Zoo: Exploring the

Reassembling the Social: An Introduction to Actor-Network-Theory by Bruno Latour,

Revisiting the QuantitativeQualitative Debate Implications for Mixed-Methods Research,” Community Health,

Social Machines: Computing means connecting,” Technology Review Published by MIT,

The Two Magics of Web Science,”

Understanding social machines

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Understanding social machines

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